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Optimal sizing of wind and solar hybrid renewable energy systems under grid constraints: A Brazilian case study

2026-08-03 · International Journal of Sustainable Energy Planning and Management

One-line summary

A solar energy research paper on Optimal sizing of wind and solar hybrid renewable energy systems under grid constraints: A Brazilian case study.

Engineering notes

Engineering notes will be added by the Power for Solar editorial team.

Chinese explanation / 中文解读

中文解读待补充:本站会优先为光伏效率、钙钛矿太阳能电池、储能技术、太阳能热利用、BIPV、并网技术等高价值论文补充中文说明。

Original abstract

The increasing demand for clean and cost-effective energy has driven the development of hybrid renewable energy systems, particularly those combining wind and solar power. This paper introduces a practical optimization model for sizing hybrid onshore wind and photovoltaic power plants, incorporating critical systemic constraints such as land availability, grid capacity, and natural complementarity between energy sources. Unlike traditional models focused solely on minimizing cost or maximizing energy output, this approach considers the temporal anti-correlation between wind and photovoltaic resources to enhance grid infrastructure utilization. Developed in Microsoft Excel® with the Solver add-in, the model is accessible and easy to implement for energy planners and developers. A real case study in Sento Sé, Bahia State in Brazil, where wind and solar generation patterns are strongly anticorrelated, demonstrates the effectiveness of the model. Results indicate that the proposed hybrid configuration reduced the annualized system cost from 237.6 M USD to 161.6 M USD compared to standalone wind solution, representing a cost reduction of approximately 32%. Furthermore, grid infrastructure utilization increased from 64% to 84%, highlighting the benefit of incorporating resource complementarity into the system sizing. These outcomes highlight the value of well-designed hybrid systems, maximizing renewable integration without overloading existing infrastructure. The model offers a replicable decision-making tool for early-stage project design and capacity expansion planning, supporting more efficient and sustainable energy transitions.

5.0Engineering value
7.0Research novelty
4.0Business relevance

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